I am a B.Tech student at IIT, Kanpur.Currently, I am doing research in the domain of nature-inspired algorithms. So, I need the immediate code of Intelligent Water Drops algorithm to carry out my stuff.
Hope you people will respond quickly.
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Introduction
Almost every IWD algorithm is composed of two parts: a graph that plays the role of distributed memory on which soils of different edges are preserved, and the moving part of the IWD algorithm, which is a few number of Intelligent water drops. These Intelligent Water Drops (IWDs) both compete and cooperate to find better solutions and by changing soils of the graph, the paths to better solutions become more reachable. It is mentioned that the IWD-based algorithms need at least two IWDs to work.
. Basic principles of the IWD algorithm
Water drops that flow in rivers, lakes, and seas are the sources of inspiration for
developing the IWD. This intelligence is more obvious in rivers which find their ways
to lakes, seas, or oceans despite many different kinds of obstacles on their ways. In the
water drops of a river, the gravitational force of the earth provides the tendency for
flowing toward the destination. If there were no obstacles or barriers, the water drops
would follow a straight path toward the destination, which is the shortest path from
the source to the destination. However, due to different kinds of obstacles in their way
to the destination, which constrain the path construction, the real path has to be
different from the ideal path and lots of twists and turns in the river path is observed.
The interesting point is that this constructed path seems to be optimum in terms of
distance from the destination and the constraints of the environment.
Imagine a water drop is going to move from a point of river to the next point in the
front as shown in Figure 1. It is assumed that each water drop flowing in a river can
carry an amount of soil which is shown by the size of the water drop in the figure. The
amount of soil of the water drop increases as it reaches to the right point shown in
Figure 1 while the soil of the river bed decreases. In fact, some amount of soil of the
river bed is removed by the water drop and is added to the soil of the water drop. This
property is embedded in the IWDs such that each IWD holds soil in itself and removes
soil from its path during movement in the environment.
The proposed IWD algorithm
The IWD (Shah-Hosseini, 2007) have been designed to imitate the prominent
properties of the natural water drops that flow in the beds of rivers. Each IWD is
assumed to have an amount of the soil it carries, soil(IWD), and its current velocity,
velocity(IWD).
The environment in which IWDs are moving is assumed to be discrete. This
environment may be considered to be composed of Nc nodes and each IWD needs to
move from one node to another. Every two nodes are linked by an arc which holds an
amount of soil. Based on the activities of the IWDs flowing in the environment, the soil
of each arc may be increased or decreased.
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Description
This project deals with the Intelligent Water Drops algorithm or the IWD algorithm. The IWD algorithm is a population & nature-inspired combinatorial optimization algorithm. It tries to imitate the behavior that natural water drops conduct in river beds where they create complex paths that seem optimistic considering the environment, obstacles, and the surrounding terrain.
One way to use the IWD algorithm is to map our optimization problem into a graph over which Intelligent Water Drops (IWDs) travel from node to node to gradually create complete solutions. During this trip, the soli of the graph deposited on the links of the graph are changed and little by little the optimal paths will hold less soil in comparison to other possible paths.
It is also possible to solve continuous optimization problems by the IWD algorithm. One attempt is the IWD-CO (IWD for Continuous Optimization)
In this project, the focus is to gradually present implemented IWD-based algorithms.
Intelligent Water Drops algorithm
Intelligent Water Drops algorithm, or the IWD algorithm,[1] is a swarm-based nature-inspired optimization algorithm. This algorithm contains a few essential elements of natural water drops and actions and reactions that occur between river's bed and the water drops that flow within. The IWD algorithm may fall into the category of Swarm intelligence and Metaheuristic. Intrinsically, the IWD algorithm can be used for Combinatorial optimization. However, it may be adapted for continuous optimization too. The IWD was first introduced for the traveling salesman problem in 2007.Since then, multitude of researchers have focused on improving the algorithm for different problems.